Modified ant colony system for coloring graphs

Ant colony system (ACS) algorithm is new meta-heuristic for hard combinational optimization problem. It is a population-based approach that uses exploitation of positive feedback as well as greedy search. Recently, various methods and solutions are proposed to solve optimal solution of graph coloring problem that assign different colors for adjacency node (vi, vj). This paper introduces ANTCOL algorithm to solve solution by ant colony system algorithm that is not known well as the solution of existent graph coloring problem. After introducing the ACS algorithm and the assignment type problem, it shows the way on how to apply ACS to solve ATP. We propose ANT_XRLF method which uses XRLF to solve the ANTCOL. Graph coloring result and the execution time of our method are compared with existent generating functions (ANT Random, ANT_LF, ANT_SL, ANT_DSATUR, and ANT_RLF method) Also we compare the existing generating functions with the method ANT_XRLF (ANT_XRLF_R) where re-search is added.